Diabetes mellitus is a significant health problem, affecting approximately 16 million people in the United States. Loss of sufficient insulin production by the pancreatic beta cell is the hallmark of type I diabetes, while in type II diabetes there is in addition peripheral insulin resistance. Future therapeutic approaches of regeneration of beta cells both in vivo and in vitro will benefit greatly from a complete understanding of the development and differentiation of the pancreatic islets. We propose to establish a functional genomics resource that will provide detailed information about the complex patterns of gene expression that govern this process. Specific aim 1 of this proposal is to develop normalized and subtracted cDNA libraries enriched for rare transcripts expressed in the developing endocrine pancreas and to determine full length sequences of previously unknown transcripts. Aim 2 is to generate cDNA microarrays representing thousands of pancreas- specific or pancreas-enriched transcripts. This microarray facility will be established within the context of the University of Pennsylvania Diabetes Center. Clones for these microarrays will be obtained from three sources: a) existing, commercially available microarrays screened with pancreas specific probes, b) the normalized newborn islet cDNA library obtained in Aim 1, and c) subtracted cDNA libraries representing rare pancreatic transcripts. The latter will take advantage of RNA amplification from single cells; which was pioneered at Penn, to generate cDNA libraries specific for the individual endocrine cell types. Thus we will be able to generate a complex microarray of thousands of cDNAs which represent both abundant and rare pancreatic mRNAs. Specific aim 3 is to determine the expression profile of thousands of genes during pancreatic development and in mice carrying mutations that affect pancreatic development and function. We will utilize the microarrays generated in aim 2 to determine expression profiles during the development of the endocrine pancreas, both in the entire pancreas as well as in individual endocrine cell lineages. We will utilize the computer resources of the University of Pennsylvania Bioinformatics Center for the efficient analysis of the large body of data generated. This bioinformatics database, as well as the microarrays, will be made available to the general research community. Establishing these state-of-the-art technologies, and applying them to the endocrine pancreas, will enable principal investigators to formulate and test novel hypotheses that address the causes and progression of diabetes.